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Predicting High Resource Use in Health Services via Explainable AI Models


   Department of Computer and Information Sciences

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  Prof Feng Dong, Prof Roma Maguire  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Background

This PhD research studentship will contribute to the research in predicting high resource use in health services via explainable AI models

A Royal College of Emergency Medicine guideline highlights that there is consistent evidence that Frequent Attenders for a department do not constitute a stable cohort. A small number of ‘very high frequency attenders’ may have different characteristics to frequent attenders who are comprised of a more stable population with a lower admission rate. Within Lanarkshire, the data indicate that the frequent attenders seen are predominantly a younger cohort (i.e. not frail elderly), vulnerable and facing the multiple challenges of deprivation and poor health, both physical and mental.

Recommendations highlight the need for a more anticipatory and predictive approach to the identification and management of frequent attendance – moving from a system that is reactive, dealing with events once thresholds are met to one that can identify a person's risk of becoming a frequent attender early in their trajectory.   Such intelligence provides information to inform interventions to provide early support, including the development of an evidence based multidisciplinary / multiagency model that leads to early management in the community and reduce unscheduled service use for these individuals and improve care for patients. This research is therefore to develop and test new explainable AI approaches to predict frequent attenders in NHS Lanarkshire.

Research Themes

The student will be asked to focus PhD research to target the use of state-of-the-art AI models to support the prediction and human centric analysis of frequent attendance. The specific objectives are:

-      To conduct requirement analysis and engage stakeholders in the co-design of the solution for clinical practice;

-      To apply explainable AI prediction model that incorporates causality structure learning together with uncertainty estimation to support prediction and human centric analysis of FA in healthcare systems

-      To validate the new technologies, test their acceptability and usability at clinical sites and explore key stakeholder perceptions

We are in collaborations with a number of clinical settings with NHS Lanarkshire.

Eligibility

·      The studentships are open to all the home, EU and International students.

·      36- month stipend, home tuition, travel and equipment are covered for successful candidates

·      Candidates need to meet the university admission criteria, which can be found in the submission link below.

Application Submission

To apply for this, follow the official link. Please include a research proposal which describes your research plan.

https://www.strath.ac.uk/studywithus/postgraduateresearch/

Cut-off Date: 6th January 2023

Contact: For further enquiries, please contact Prof. Feng Dong, [Email Address Removed]

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